class_docstr: Class with all code to run experiment.
class_docstr_tok: ["Class","with","all","code","to","run","experiment","."]
code: def evaluate_batch(self, images, labels):
      logits = self.model(images, training=False)
      num_correct = jn.count_nonzero(
          jn.equal(jn.argmax(logits, axis=1), labels)
      )
      return num_correct
  
file_path: objax/examples/image_classification/imagenet_resnet50_train.py
imports: import os
  import time
  import jax
  import jax.numpy
  import numpy
  from absl import app, flags, logging
  import objax
  from examples.image_classification import imagenet_resnet50_data
  from objax.zoo.resnet_v2 import ResNet50
label_desc: Use image node_id 2 for calling the Experiment obj's underlying member method code with example usage: obj.evaluate_batch(images, labels) and returns: num_correct